{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Custom finite difference coefficients in Devito\n",
    "\n",
    "## Introduction\n",
    "\n",
    "When taking the numerical derivative of a function in Devito, the default behaviour is for 'standard' finite difference weights (obtained via a Taylor series expansion about the point of differentiation) to be applied. Consider the following example for some field $u(\\mathbf{x},t)$, where $\\mathbf{x}=(x,y)$. Let us define a computational domain/grid and differentiate our field with respect to $x$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from devito import Grid, TimeFunction\n",
    "\n",
    "# Create our grid (computational domain)\n",
    "Lx = 10\n",
    "Ly = Lx\n",
    "Nx = 11\n",
    "Ny = Nx\n",
    "dx = Lx/(Nx-1)\n",
    "dy = dx\n",
    "grid = Grid(shape=(Nx,Ny), extent=(Lx,Ly))\n",
    "\n",
    "# Define u(x,y,t) on this grid\n",
    "u = TimeFunction(name='u', grid=grid, time_order=2, space_order=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, lets look at the output of $\\partial u/\\partial x$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-u(t, x, y)/h_x + u(t, x + h_x, y)/h_x\n"
     ]
    }
   ],
   "source": [
    "print(u.dx.evaluate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default the 'standard' Taylor series expansion result, where `h_x` represents the $x$-direction grid spacing, is returned. However, there may be instances when a user wishes to use 'non-standard' weights when, for example, implementing a dispersion-relation-preserving (DRP) scheme. See e.g. \n",
    "\n",
    "[1] Christopher K.W. Tam, Jay C. Webb (1993). ”Dispersion-Relation-Preserving Finite Difference Schemes for Computational Acoustics.” **J. Comput. Phys.**, 107(2), 262--281. https://doi.org/10.1006/jcph.1993.1142\n",
    "\n",
    "for further details. The use of such modified weights is facilitated in Devito via the 'symbolic' finite difference coefficents functionality. Let us start by re-defining the function $u(\\mathbf{x},t)$ in the following manner:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "u = TimeFunction(name='u', grid=grid, time_order=2, space_order=2, coefficients='symbolic')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the addition of the `coefficients='symbolic'` keyword. Now, when printing $\\partial u/\\partial x$ we obtain:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "W(x, 1, u(t, x, y), x)*u(t, x, y) + W(x - h_x, 1, u(t, x, y), x)*u(t, x - h_x, y) + W(x + h_x, 1, u(t, x, y), x)*u(t, x + h_x, y)\n"
     ]
    }
   ],
   "source": [
    "print(u.dx.evaluate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Owing to the addition of the `coefficients='symbolic'` keyword the weights have been replaced by sympy functions. Now, take for example the weight `W(x - h_x, 1, u(t, x, y), x)`, the notation is as follows:\n",
    "* The first `x - h_x` refers to the spatial location of the weight w.r.t. the evaluation point `x`.\n",
    "* The `1` refers to the order of the derivative.\n",
    "* `u(t, x, y)` refers to the function with which the weight is associated.\n",
    "* Finally, the `x` refers to the dimension along which the derivative is being taken.\n",
    "\n",
    "Symbolic coefficients can then be manipulated using the Devito 'Coefficient' and 'Substitutions' objects. First, let us consider an example where we wish to replace the coefficients with a set of constants throughout the entire computational domain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from devito import Coefficient, Substitutions # Import the Devito Coefficient and Substitutions objects\n",
    "# Grab the grid spatial dimensions: Note x[0] will correspond to the x-direction and x[1] to y-direction\n",
    "x = grid.dimensions \n",
    "# Form a Coefficient object and then a replacement rules object (to pass to a Devito equation):\n",
    "u_x_coeffs = Coefficient(1, u, x[0], np.array([-0.6, 0.1, 0.6]))\n",
    "coeffs = Substitutions(u_x_coeffs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Devito Coefficient ojects take arguments in the following order:\n",
    "1. Derivative order (in the above example this is the first derivative)\n",
    "2. Function to which the coefficients 'belong' (in the above example this is the time function `u`)\n",
    "3. Dimension on which coefficients will be applied (in the above example this is the x-direction)\n",
    "4. Coefficient data. Since, in the above example, the coefficients have been applied as a 1-d numpy array replacement will occur at the equation level. (Note that other options are in development and will be the subject of future notebooks)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, lets form a Devito equation, pass it the Substitutions object, and take a look at the output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eq(0.1*u(t, x, y) - 0.6*u(t, x - h_x, y) + 0.6*u(t, x + h_x, y) - u(t - dt, x, y)/(2*dt) + u(t + dt, x, y)/(2*dt), 0)\n"
     ]
    }
   ],
   "source": [
    "from devito import Eq\n",
    "eq = Eq(u.dt+u.dx, coefficients=coeffs)\n",
    "print(eq.evaluate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that in the above equation the standard weights for the first derivative of `u` in the $x$-direction have now been replaced with our user defined weights. Note that since no replacement rules were defined for the time derivative (`u.dt`) standard weights have replaced the symbolic weights.\n",
    "\n",
    "Now, let us consider a more complete example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example: Finite difference modeling for a large velocity-contrast acousitc wave model\n",
    "\n",
    "It is advised to read through the 'Introduction to seismic modelling' notebook located in  devito/examples/seismic/tutorials/01_modelling.ipynb before proceeding with this example since much introductory material will be ommited here. The example now considered is based on an example introduced in\n",
    "\n",
    "[2] Yang Liu (2013). ”Globally optimal finite-difference schemes based on least squares.” **GEOPHYSICS**, 78(4), 113--132. https://doi.org/10.1190/geo2012-0480.1.\n",
    "\n",
    "See figure 18 of [2] for further details. Note that here we will simply use Devito to 'reproduce' the simulations leading to two results presented in the aforementioned figure. No analysis of the results will be carried out. The domain under consideration has a sptaial extent of $2km \\times 2km$ and, letting $x$ be the horizontal coordinate and $z$ the depth, a velocity profile such that $v_1(x,z)=1500ms^{-1}$ for $z\\leq1200m$ and $v_2(x,z)=4000ms^{-1}$ for $z>1200m$.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Operator `initdamp` run in 0.01 s\n",
      "Operator `padfunc` run in 0.01 s\n"
     ]
    },
    {
     "data": {
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cAexFsRjWIuA4238c+2NExEQ2iEMCW02QPVojvjUtJ468stwiItYxaDXGXqnzgXfXylW57pXUcv0YFf61XPXr1uZPhCQdL+l35XZ8P8sZEd0bsHeMPdHXwAiczcgvOo8A9iy3WcBXAMqZdk8F9gemA6eW7woiYoA0VgkcwCGBY9LXwGj7OtpPPQ7Fql/nunA9sI2k7YFXA1faXmb7QYqmfK1lDyNiwxnUIYGSPivpRd2eX2eVwM2BN7L+MoSntTtnFNau+lVaUqa1S29VvlkUtU2KJSAiYkMa0Kbyb4DZ5dow3wTOt/1w3ZPrhPIfAA9TfLKzokPe0Wq36lft1cDKJRhnA0g7ZMGuiA1oFMunblC2vw58XdLzKeZ7uFXSz4Gv2b6m0/l1AuNOtvvVjF276lfjXsDSMv2gSvpP+lSGiOhS4x3jICrXj/mzcrsfuAX4oKR32x5pvZha7xh/0TyvWY/NBd5W9k6/DHjY9j3AFcBhkrYtO10OK9MiYoAM8DvGz1M0p48EPml7P9ufsv1aWqwtUzXS7DqNWSo2BU6QdCdFU7qxtEHHWSoknU9R85sqaQlFT/NkigucRfER5pHAYoqFa04ojy2T9AngxvJSp9keqRMnIsbJgL5jvA34R9utFsSa3unkkUL5mGepsH1sh+OmWFOm1bE5wJyxliEi+meAP/B+SxlD1pL0H7ZfWacTZqQhgf9ZXuxbto+r3OBbwHEtT4yIjcagvWOUNAXYgqKVui1PdeT+CbBD3evUafyv8y1Q+UJzv7o3iIjhVfRKD9RY6XcDJ1EEwebJtJcDZ9a9yEjvGE8GPgo8TdJynoq8Kyk/j4mIjdugNaVtfxH4oqS/tv2lbq8zUlP6n4F/lvTPtk/u9gYRMdwGKTBKOsT21cB/SXpD9bjt79e5Tp2m9EfLG7ycopf6p7a7Xsg6IobHoL1jpJgr9mqg1RrSBnoWGM+kmJz2/HL/PZIOtd2yNzkiNh6DtuaL7VPLP08Yy3XqPNGBwIvLT2uQdA6wYCw3jYjhMKhDAiV9Evi07YfK/W2BD9n+xzrn1xn5cgewS9P+zsCtoy1oRAyfAZ527IhGUAQoZ+k6su7JdWqMzwAWSfpVuf9S4JeS5pY3PGoUhY2IITNITekmkyRtbnsFgKSnQf3viuo80Sndliwihtugfa7T5NvAf0j6JkWny/8Gzql7csfAaPtaSbsCe9q+qoy8m9p+pNsSR8RwGNTAaPvTkm4FXlUmfcJ27Ylo6kxU+y6KiWC3A55LMQXYWcArR1/ciBg2A/a5TrNfU0xa4/J3bXU6X95PsXzqcgDbvwOeNcoCRsQQWsMmrGTzjtuGJulNwK+AY4A3ATdIOqbu+XXeMa6wvVJS44ab0mY27YjY+PSiKS1pZ+Bc4NnAGmB2ObyvOc9BFCsK3FUmfX+EJVb+AXip7XvLc58JXAVcWKc8dQLjtZIaY6YPBd4H/LDOxSNiuPXwHeMqiu8Mb5K0FTBf0pW2b6/k+6ntOlMibtIIiqUHGMXif3UC40eAd1B81P1uisllv173BhExvExv3jGWM/ffU/5+RNIiigXwqoGxrh9JuoKnRuy9mSJ21VKnV3qNpEuAS2zf110ZN4ztuYdZfHy8ixExtNafVqv2kMCpkuY1X6pcyG79K0q7USw/cEOLwwdIuoVibai/s72w1TVs/72kN1L0j6i838V1CgojTzsmiqUITiwvLEmrgS/1aOnUiJjgRtGUvt/2tE6ZJD0duAg4yfbyyuGbgF1tPyrpSOASYM+2ZbMvKq81aiO1uU+iiLYvtf0M29sB+wMzJH2g04UlzZF0r6Tb2hx/i6Rby+0Xkl7SdOwPkhZIurnyr0xEDBAjVrBZx60OSZMpAtl5raYHs73c9qPl78uAyZKmVq7xiKTlLbZHynllaxmpDvw24FDb9zcV7E5JbwV+DHyhw7XPBs6g6Glq5S7gQNsPSjqCopa+f9Pxg5vvHRGDp1ez65Qt1G8Ai2x/vk2eZwP/bduSplNU7B5Ypzz2VmMuDCMHxsmtApPt+8rIPiLb15XvCtod/0XT7vUUH45HxATTo17pGRTrSC2QdHOZ9lHKCWzKVUWPAd4raRXwODCzMetXK5JeTjFi75tlzXIr23e1y99spMC4sstj3XgHcHnTvoEfSzLw1XYvaQEkzaIYmcPWPS5URIysV5/r2P4ZTy2f0i7PGRSt0I4knQpMA54PfBPYjGL89Iw6548UGF/Spk0uYEqdi9ch6WCKwPjypuQZtpdKehZwpaTf2L6u1fll0JwNsEMRSCNiAzFi9ZqBHBL4eoqe7ZsAynhSu5k90povfX9aSXtRfBN5hO217wpsLy3/vFfSxRQLZLcMjBExfrxGrHhioFYJbFhZvotsTLC95WhOrv0leK9J2oVi/YXjbP+2KX3LRmQvH+YwoGXPdkSML1usXjWp4zYOvifpq8A25UQ4VwFfq3ty32aYlHQ+cBDFh51LKL6JnAxrX6SeQjEJ7pfLcdiryu+c/hS4uEzbFPiO7R/1q5wRMQZmvALfiGx/thzCvJziPeMptq+se37fAqPtYzscfyfwzhbpdwIvWf+MiBg0tlj15OAERklnUFSmflEGwtrBsNlAzkkeEROFWLN6oMLI74DPSdoe+C5wvu2bO5yznnF7xxgRQ8DAqkmdtw1VHPuLtg+gWN10GfBNSYsknSLpeXWvk8AYEd1bI3hi087bBmb7P21/yvY+wF9RfL6zqO75CYwRMTaramwbmKTJkl4r6TyKwSO/Bd5Y9/yBejkQERNMMSHjwCh7oo8F/pJiaYMLgFm2/2c010lgjIjuDVhgpBhf/R2KuRqXdXuRBMaI6J6BJ8e7EE+xfXAvrpPAGBHdM7BivAvRewmMEdG9wWtK90QCY0R0L4ExIqIigTEioiKBMSKihQTGiIgma4AnxrsQvZfAGBHdS1M6IqIigTEioiKBMSKihSEMjH2bdkzSHEn3Smq5kJWkgyQ9LOnmcjul6djhku6QtFjSR/pVxogYo0aNccCmHRurftYYz6ZYHPvcEfL81PZrmhMkTQLOBA4FlgA3Sppr+/Z+FTQiurQGeHy8C9F7fasx2r6OYmrx0ZoOLLZ9p+2VFPOpHd3TwkVEbxhYXWObYMZ7Bu8DJN0i6XJJLyrTdgTubsqzpExrSdIsSfMkzXusnyWNiNbSlO6pm4BdbT8q6UjgEmBPQC3yut1FbM8GZgPsILXNFxF9MKS90uNWY7S93Paj5e/LgMmSplLUEHduyroTsHQcihgRnaTzpbckPRv4b9uWNJ0iSD8APATsKWl34L+AmRSrfEXEoMmQwNGRdD5wEDBV0hLgVGAygO2zgGOA90paRdGvNdO2gVWSTgSuACYBc2wv7Fc5I2KMJmCNsJO+BUbbx3Y4fgbF5zytjl0GXNaPckVEDw3pO8aMfImI7g3YYli9ksAYEd1rfMc4ZMb7O8aImMh61CstaWdJ10haJGmhpL9tkUeS/rUcKnyrpH17+CTrSI0xIrpnejUkcBXwIds3SdoKmC/pyspQ4CMovnXeE9gf+Er5Z8+lxhgR3evRkEDb99i+qfz9CLCI9Ue8HQ2c68L1wDaStu/Ng6wrNcaI6F79XumpkuY17c8uR62tR9JuwD7ADZVD7YYL31OvsPUlMEZE9+oHxvttT+uUSdLTgYuAk2wvrx5uU4KeS2CMiO718HMdSZMpguJ5tr/fIssGGy6cd4wRMTY9eMcoScA3gEW2P98m21zgbWXv9MuAh233vBkNqTFGxFj0bqz0DOA4YIGkm8u0jwK7wNphxJcBRwKLgceAE3py5xYSGCOiez1qStv+Ga3fITbnMfD+sd+tswTGiOjekI58SWCMiLHJJBIREU0yu05EREUmqo2IqEiNMSKihQTGiIgmmah2dCTNAV4D3Gv7xS2O/z3wlqZyvAB4pu1lkv4APELxIcCqOmMsI2IcDOnnOv0cEng2cHi7g7Y/Y3tv23sDJwPX2l7WlOXg8niCYsSgyvKpo2P7unL6oDqOBc7vV1kiok/W0KuJagfKuE8iIWkLiprlRU3JBn4sab6kWeNTsoiopQeTSAyaQeh8eS3w80ozeobtpZKeBVwp6Te2r2t1chk4ZwFs3f+yRkRVX2ZEHF/jXmMEZlJpRtteWv55L3AxML3dybZn255me9oWfS1mRGwsxjUwStoaOBD4QVPaluViOEjaEjgMuG18ShgRG6N+fq5zPnAQxVoPS4BTgcmwdm41gNcDP7b9P02n/ilwcTFvJZsC37H9o36VMyKiqp+90sfWyHM2xWc9zWl3Ai/pT6kioreGs1t6EDpfImLCGs6hLwmMETEGwzmLRAJjRIxBaowRERUJjBERFSadLxER68g7xoiIijSlIyIqUmOMiKhIjTEioiI1xoiIigwJjIioSFM6IqKFNKUjIpqkxhgRUZHAGBFRkV7piIiK9EpHRFSkKR0RUTGcTem+rRIoaWdJ10haJGmhpL9tkUeS/lXSYkm3Stq36djxkn5Xbsf3q5wRMRaNGmOnrTNJcyTdK6nlqqCSDpL0sKSby+2UXjxBK/2sMa4CPmT7pnI51PmSrrR9e1OeI4A9y21/4CvA/pK2o1hVcBrF3/x8SXNtP9jH8kbEqPW0xng2cAZw7gh5fmr7Nb26YTt9qzHavsf2TeXvR4BFwI6VbEcD57pwPbCNpO2BVwNX2l5WBsMrgcP7VdaI6Faj86XT1pnt64BlfSnmKG2Qd4ySdgP2AW6oHNoRuLtpf0mZ1i691bVnAbPK3RUfh5bV8AluKnD/eBeiD4b1uWB4n+356+7ecwV8bGqN86ZImte0P9v27C7uf4CkW4ClwN/ZXtjFNTrqe2CU9HTgIuAk28urh1uc4hHS108s/nJnl/eaZ3vaGIo7kPJcE8+wPlsluGF7Q7bkbgJ2tf2opCOBSyhew/Vc35rSAJImUwTF82x/v0WWJcDOTfs7UfxL0C49IjZStpfbfrT8fRkwWVKd2uqo9bNXWsA3gEW2P98m21zgbWXv9MuAh23fA1wBHCZpW0nbAoeVaRGxkZL07DKuIGk6Rfx6oB/36mdTegZwHLBA0s1l2keBXQBsnwVcBhwJLAYeA04ojy2T9AngxvK802zXeSnbzTuLiSDPNfEM67P17bkknQ8cBEyVtITiy5TJsDZeHAO8V9Iqih6dmbZbvmIbc1n6dN2IiAmrr+8YIyImogTGiIiKCRcYJR0u6Y5yGOFHWhzfXNJ3y+M3lN9QTgg1nu3tku5rGhL1zvEo52jUGObVdljooBukIWy9NNbhvEPB9oTZgEnA74HnAJsBtwAvrOR5H3BW+Xsm8N3xLncPn+3twBnjXdZRPtdfAPsCt7U5fiRwOcW3qy8DbhjvMvfw2Q4CLh3vcnbxXNsD+5a/twJ+2+J/ixP2v1udbaLVGKcDi23faXslcAHFsMJmRwPnlL8vBF7Z6OIfcHWebcJx52Fe7YaFDrwazzYheWzDeYfCRAuMdYYKrs1jexXwMPCMDVK6sak7DPKNZdPlQkk7tzg+0dQe/jlBHSDpFkmXS3rReBdmtLoYzjsUJlpgrDNUsPZwwgFTp9w/BHazvRdwFU/VjCeyifrfq47GELaXAF+iGMI2YXQ5nHcoTLTAWGeo4No8kjYFtmZiNHc6PpvtB2yvKHe/Buy3gcrWT0M7/NMbcAhbr41hOO9QmGiB8UZgT0m7S9qMonNlbiXPXKAxse0xwNUu3xYPuI7PVnmHcxTFu5+Jrt2w0AlvQw5h66UxDucdChNqaQPbqySdSDFuehIwx/ZCSacB82zPpfgP+i1JiylqijPHr8T11Xy2v5F0FMXMoMsoeqkHWo1hXi2HhU4EgzSErce6Hs47LDIkMCKiYqI1pSMi+i6BMSKiIoExIqIigTEioiKBMSKiIoFxI1DOlnKXivW6KZeMuEvSrn2633skva38/XZJOzQd+7qkF/boPq9rzFgj6WxJx3R5nWdK+lEvyhTDIYFxI2D7buArwOll0ukUy1f+Z5/ud5btxqLpbwd2aDr2Ttu39+hWHwa+PNaL2L4PuEfSjLEXKYZBAuPG4wvAyySdBLwc+Fw1g6TdJP1G0jlNE1VsUR57paRfS1pQzkO4eZkD/mDkAAACvklEQVR+uqTby/yfLdM+JunvyhrcNOC8cj7Cp0n6iaRpZb5jy+vdJulTTeV4VNI/lZMvXC/pT1uU9XnACtvrrd0s6RNlDXITSX+Q9ElJv5Q0T9K+kq6Q9HtJ72k67RLgLd3/9cYwSWDcSNh+Evh7igB5Ujm1WSvPp6hN7gUsB94naQpwNvBm239OMWLqvWXT/PXAi8r8/7dyzwuBecBbbO9t+/HGsbJ5/SngEGBv4KWSXlce3hK4vpx84TrgXS3KOYNikoZ1SPo08CzgBNtryuS7bR8A/LR8jmMo5hA8renUecAr2vydxEYmgXHjcgRwD/DiEfLcbfvn5e9vU9Qunw/cZfu3Zfo5FJO0LgeeAL4u6Q0UQ8PqeinwE9v3ldPDnVdeE2AlcGn5ez6wW4vztwfuq6T9H2Ab2++uDL1rjDlfQDGh6iNl8/kJSduUx+6lqckfG7cExo2EpL2BQylqSh8YYVLR6hhR03qKqcZ8l9MpZmF5HTCaDoyRJg9+simwrab1mP7HgSmVtBuB/RqdTE0aMxKtafrd2G9ce0p5zYgExo1BOVvKVyia0H8EPgN8tk32XSQdUP4+FvgZ8BtgN0l7lOnHAdeW8/VtXU6pdRJFk7jqEYrp8atuAA6UNFXSpPJe147isRYBe1TSfkTRsfTvklrdcyTPA1qu3RIbnwTGjcO7gD/avrLc/zLwZ5IObJF3EXC8pFuB7YCv2H6CYvaUf5O0gKKmdRZFwLu0zHst8IEW1zsbOKvR+dJILKeoOhm4hmJ9m5ts/2AUz3QdsE9jWq+m6/4bxVyVc5vvV8PBwL+PIn8MscyuE2upmMb+UtsjvYMcGJK+CPzQ9lU9uNZ1wNG2Hxx7yWKiS40xJrJPAluM9SKSngl8PkExGlJjjIioSI0xIqIigTEioiKBMSKiIoExIqIigTEiouL/A9SzxKEp1rKXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#NBVAL_IGNORE_OUTPUT\n",
    "from examples.seismic import Model, plot_velocity\n",
    "%matplotlib inline\n",
    "\n",
    "# Define a physical size\n",
    "Lx = 2000\n",
    "Lz = Lx\n",
    "h = 10\n",
    "Nx = int(Lx/h)+1\n",
    "Nz = Nx\n",
    "\n",
    "shape = (Nx, Nz)  # Number of grid point\n",
    "spacing = (h, h)  # Grid spacing in m. The domain size is now 2km by 2km\n",
    "origin = (0., 0.)\n",
    "\n",
    "# Define a velocity profile. The velocity is in km/s\n",
    "v = np.empty(shape, dtype=np.float32)\n",
    "v[:, :121] = 1.5\n",
    "v[:, 121:] = 4.0\n",
    "\n",
    "# With the velocity and model size defined, we can create the seismic model that\n",
    "# encapsulates these properties. We also define the size of the absorbing layer as 10 grid points\n",
    "nbl = 10\n",
    "model = Model(vp=v, origin=origin, shape=shape, spacing=spacing,\n",
    "              space_order=20, nbl=nbl)\n",
    "\n",
    "plot_velocity(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The seismic wave source term will be modelled as a Ricker Wavelet with a peak-frequency of $25$Hz located at $(1000m,800m)$. Before applying the DRP scheme, we begin by generating a 'reference' solution using a spatially high-order standard finite difference scheme and time step well below the model's critical time-step. The scheme will be 2nd order in time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from examples.seismic import TimeAxis\n",
    "\n",
    "t0 = 0.  # Simulation starts a t=0\n",
    "tn = 500.  # Simulation lasts 0.5 seconds (500 ms)\n",
    "dt = 0.2  # Time step of 0.2ms\n",
    "\n",
    "time_range = TimeAxis(start=t0, stop=tn, step=dt)\n",
    "\n",
    "#NBVAL_IGNORE_OUTPUT\n",
    "from examples.seismic import RickerSource\n",
    "\n",
    "f0 = 0.015  # Source peak frequency is 25Hz (0.025 kHz)\n",
    "src = RickerSource(name='src', grid=model.grid, f0=f0,\n",
    "                   npoint=1, time_range=time_range)\n",
    "\n",
    "# First, position source centrally in all dimensions, then set depth\n",
    "src.coordinates.data[0, :] = np.array(model.domain_size) * .5\n",
    "src.coordinates.data[0, -1] = 800.  # Depth is 800m\n",
    "\n",
    "# We can plot the time signature to see the wavelet\n",
    "src.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let us define our wavefield and PDE:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the wavefield with the size of the model and the time dimension\n",
    "u = TimeFunction(name=\"u\", grid=model.grid, time_order=2, space_order=20)\n",
    "\n",
    "# We can now write the PDE\n",
    "pde = model.m * u.dt2 - u.laplace + model.damp * u.dt\n",
    "\n",
    "# This discrete PDE can be solved in a time-marching way updating u(t+dt) from the previous time step\n",
    "# Devito as a shortcut for u(t+dt) which is u.forward. We can then rewrite the PDE as \n",
    "# a time marching updating equation known as a stencil using customized SymPy functions\n",
    "from devito import solve\n",
    "\n",
    "stencil = Eq(u.forward, solve(pde, u.forward))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Finally we define the source injection and receiver read function to generate the corresponding code\n",
    "src_term = src.inject(field=u.forward, expr=src * dt**2 / model.m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, lets create the operator and execute the time marching scheme:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from devito import Operator\n",
    "\n",
    "op = Operator([stencil] + src_term, subs=model.spacing_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Operator `Kernel` run in 2.51 s\n"
     ]
    }
   ],
   "source": [
    "#NBVAL_IGNORE_OUTPUT\n",
    "op(time=time_range.num-1, dt=dt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And plot the result:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "Lx = 2000\n",
    "Lz = 2000\n",
    "\n",
    "abs_lay = nbl*h\n",
    "\n",
    "dx = h\n",
    "dz = dx\n",
    "X, Z = np.mgrid[-abs_lay: Lx+abs_lay+1e-10: dx, -abs_lay: Lz+abs_lay+1e-10: dz]\n",
    "\n",
    "levels = 100\n",
    "\n",
    "fig = plt.figure(figsize=(14, 7))\n",
    "ax1 = fig.add_subplot(111)\n",
    "cont = ax1.contourf(X,Z,u.data[0,:,:], levels, cmap=cm.binary)\n",
    "fig.colorbar(cont)\n",
    "ax1.axis([0, Lx, 0, Lz])\n",
    "ax1.set_xlabel('$x$')\n",
    "ax1.set_ylabel('$z$')\n",
    "ax1.set_title('$u(x,z,500)$')\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will now reimplement the above model applying the DRP scheme presented in [2].\n",
    "\n",
    "First, since we wish to apply different custom FD coefficients in the upper on lower layers we need to define these two 'subdomains' using the `Devito SubDomain` functionality:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from devito import SubDomain\n",
    "\n",
    "# Define our 'upper' and 'lower' SubDomains:\n",
    "class Upper(SubDomain):\n",
    "    name = 'upper'\n",
    "    def define(self, dimensions):\n",
    "        x, z = dimensions\n",
    "        # We want our upper layer to span the entire x-dimension and all\n",
    "        # but the bottom 80 (+boundary layer) cells in the z-direction, which is achieved via\n",
    "        # the following notation:\n",
    "        return {x: x, z: ('left', 80+nbl)}\n",
    "    \n",
    "class Lower(SubDomain):\n",
    "    name = 'lower'\n",
    "    def define(self, dimensions):\n",
    "        x, z = dimensions\n",
    "        # We want our lower layer to span the entire x-dimension and all\n",
    "        # but the top 121 (+boundary layer) cells in the z-direction.\n",
    "        return {x: x, z: ('right', 121+nbl)}\n",
    "\n",
    "# Create these subdomains:\n",
    "ur = Upper()\n",
    "lr = Lower()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now create our model incoporating these subdomains:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": [
     "nbval-ignore-output"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Operator `initdamp` run in 0.01 s\n",
      "Operator `padfunc` run in 0.01 s\n"
     ]
    }
   ],
   "source": [
    "#NBVAL_IGNORE_OUTPUT\n",
    "# Our scheme will now be 10th order (or less) in space.\n",
    "order = 10\n",
    "\n",
    "# Create our model passing it our 'upper' and 'lower' subdomains: \n",
    "model = Model(vp=v, origin=origin, shape=shape, spacing=spacing,\n",
    "              space_order=order, nbl=nbl, subdomains=(ur,lr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And re-define model related objects. Note that now our wave-field will be defined with `coefficients='symbolic'`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "t0 = 0.  # Simulation starts a t=0\n",
    "tn = 500.  # Simulation last 1 second (500 ms)\n",
    "dt = 1.0  # Time step of 1.0ms\n",
    "\n",
    "time_range = TimeAxis(start=t0, stop=tn, step=dt)\n",
    "\n",
    "f0 = 0.025  # Source peak frequency is 25Hz (0.025 kHz)\n",
    "src = RickerSource(name='src', grid=model.grid, f0=f0,\n",
    "                   npoint=1, time_range=time_range)\n",
    "\n",
    "src.coordinates.data[0, :] = np.array(model.domain_size) * .5\n",
    "src.coordinates.data[0, -1] = 800.  # Depth is 800m\n",
    "\n",
    "# New wave-field\n",
    "u_DRP = TimeFunction(name=\"u_DRP\", grid=model.grid, time_order=2, space_order=order, coefficients='symbolic')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now create a stencil for each of our 'Upper' and 'Lower' subdomains defining different custom FD weights within each of these subdomains."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The underlying pde is the same in both subdomains\n",
    "pde_DRP = model.m * u_DRP.dt2 - u_DRP.laplace + model.damp * u_DRP.dt\n",
    "\n",
    "# Define our custom FD coefficients:\n",
    "x, z = model.grid.dimensions\n",
    "# Upper layer\n",
    "weights_u = np.array([ 2.00462e-03, -1.63274e-02,  7.72781e-02, \n",
    "                      -3.15476e-01,  1.77768e+00, -3.05033e+00,  \n",
    "                       1.77768e+00, -3.15476e-01,  7.72781e-02, \n",
    "                      -1.63274e-02,  2.00462e-03])\n",
    "# Lower layer\n",
    "weights_l = np.array([  0.      ,  0.      ,  0.0274017, \n",
    "                       -0.223818,  1.64875 , -2.90467,  \n",
    "                        1.64875 , -0.223818,  0.0274017,  \n",
    "                        0.      ,  0.       ])\n",
    "# Create the Devito Coefficient objects:\n",
    "ux_u_coeffs = Coefficient(2, u_DRP, x, weights_u/x.spacing**2)\n",
    "uz_u_coeffs = Coefficient(2, u_DRP, z, weights_u/z.spacing**2)\n",
    "ux_l_coeffs = Coefficient(2, u_DRP, x, weights_l/x.spacing**2)\n",
    "uz_l_coeffs = Coefficient(2, u_DRP, z, weights_l/z.spacing**2)\n",
    "# And the replacement rules:\n",
    "coeffs_u = Substitutions(ux_u_coeffs,uz_u_coeffs)\n",
    "coeffs_l = Substitutions(ux_l_coeffs,uz_l_coeffs)\n",
    "# Create a stencil for each subdomain:\n",
    "stencil_u = Eq(u_DRP.forward, solve(pde_DRP, u_DRP.forward), subdomain = model.grid.subdomains['upper'],\n",
    "               coefficients=coeffs_u)\n",
    "stencil_l = Eq(u_DRP.forward, solve(pde_DRP, u_DRP.forward), subdomain = model.grid.subdomains['lower'],\n",
    "               coefficients=coeffs_l)\n",
    "\n",
    "# Source term:\n",
    "src_term = src.inject(field=u_DRP.forward, expr=src * dt**2 / model.m)\n",
    "\n",
    "# Create the operator, incoporating both upper and lower stencils:\n",
    "op = Operator([stencil_u, stencil_l] + src_term, subs=model.spacing_map)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now execute the operator:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Operator `Kernel` run in 0.10 s\n"
     ]
    }
   ],
   "source": [
    "#NBVAL_IGNORE_OUTPUT\n",
    "op(time=time_range.num-1, dt=dt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And plot the new results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 7))\n",
    "ax1 = fig.add_subplot(111)\n",
    "cont = ax1.contourf(X,Z,u_DRP.data[0,:,:], levels, cmap=cm.binary)\n",
    "fig.colorbar(cont)\n",
    "ax1.axis([0, Lx, 0, Lz])\n",
    "ax1.set_xlabel('$x$')\n",
    "ax1.set_ylabel('$z$')\n",
    "ax1.set_title('$u_{DRP}(x,z,500)$')\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, for comparison, lets plot the difference between the standard 20th order and optimized 10th order models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 7))\n",
    "ax1 = fig.add_subplot(111)\n",
    "cont = ax1.contourf(X,Z,abs(u_DRP.data[0,:,:]-u.data[0,:,:]), levels, cmap=cm.binary)\n",
    "fig.colorbar(cont)\n",
    "ax1.axis([0, Lx, 0, Lz])\n",
    "ax1.set_xlabel('$x$')\n",
    "ax1.set_ylabel('$z$')\n",
    "\n",
    "plt.gca().invert_yaxis()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#NBVAL_IGNORE_OUTPUT\n",
    "\n",
    "# Wavefield norm checks\n",
    "assert np.isclose(np.linalg.norm(u.data[-1]), 138.987, atol=0, rtol=1e-4)\n",
    "assert np.isclose(np.linalg.norm(u_DRP.data[-1]), 83.636, atol=0, rtol=1e-4)"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
